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Related Experiment Videos

Association studies under general disease models.

D M Nielsen1, B S Weir

  • 1Program in Statistical Genetics, Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695-7566, USA.

Theoretical Population Biology
|February 22, 2002
PubMed
Summary

Genetic marker association studies help locate disease genes by analyzing linkage disequilibrium. This study clarifies how complex genetic interactions affect these association mapping methods, including marker haplotypes.

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Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Association studies aim to locate disease genes by leveraging the relationship between genetic markers and disease status.
  • This relationship is often assumed to be proportional to linkage disequilibrium (LD) and inversely related to recombination.
  • However, for disease genes with multiple alleles, the association measure is a complex weighted average of LDs, complicating the direct relationship with recombination.

Purpose of the Study:

  • To develop a general framework for examining association mapping methods.
  • To clarify the nature of case-control and transmission/disequilibrium tests.
  • To reveal the relationship between association measures and linkage disequilibrium coefficients, considering additive and nonadditive genetic effects.

Main Methods:

Related Experiment Videos

  • Utilizing a general theoretical framework to analyze association mapping.
  • Examining the impact of additive and nonadditive genetic effects on test behaviors.
  • Extending concepts to marker haplotypes for two-locus analyses.

Main Results:

  • Demonstrated that for multi-allele disease genes, association is a weighted average of LDs, not simply related to recombination.
  • Clarified the behavior of case-control and transmission/disequilibrium tests under various genetic models.
  • Showed that two-locus marker haplotype association depends on three-locus disequilibria.

Conclusions:

  • The study provides a clearer understanding of association mapping principles, especially for complex genetic scenarios.
  • The framework helps interpret results from various association tests and their dependence on LD.
  • Marker haplotype analyses are likely to offer valuable insights in future association mapping studies.